Wireless communications

ABSTRACT

A wireless system (e.g., Bluetooth, WCDMA, etc.) with multiple antenna communication channel eigenvector weighted transmissions including possibly differing order symbol constellations for differing eigenvectors. Comparison of maximizations of minimum received symbol distances provides for selection of eigenvector combinations and symbol constellations.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority from provisional applicationSer. No. 60/195,927, filed Apr. 10, 2000. The following patentapplications disclose related subject matter: Ser. Nos. 09/634,473 and09/634,819, both filed Aug.8, 2000. These referenced applications have acommon assignee with the present application.

BACKGROUND OF THE INVENTION

[0002] The invention relates to electronic devices, and moreparticularly to wireless communication.

[0003] Demand for wireless information services via cell phones andpersonal digital assistants (PDAs) is rapidly growing, and techniquesand protocols for Internet access have problems such as the delaybetween requests for web pages which primarily derives from lowtransmission data rates. Wireless Application Protocol (WAP) attempts toovercome this web page delay problem by transmitting a group of webpages as a deck of cards with each card corresponding to a page ofstructured content and navigation specifications. Each WAP card hascombined the data to be displayed with formatting instructions used incontrolling the display of the data and thus causing larger thannecessary data downloads for a fixed display format.

[0004] An alternative employs broadband wireline Internet access to alocal access point and then uses Bluetooth™ wireless connection for thelast link to an Internet appliance. The current Bluetooth gross(including overhead) speed of a 1 Mbps channel rate suffices for a 56kbps wireline (phone line) connection at home. However, with broadbandwireline connection to a Bluetooth access point in a home wireless LAN:creates a demand for high data rate Bluetooth.

[0005] Bluetooth is a system that operates in the ISM unlicensed band at2.4 GHz. Slow frequency hopping (1600 hops per second) is used to combatinterference and multipath fading: typically 79 channels are available(only 23 channels in France and Spain). The gross bit rate is 1 Mbps(maximal symmetrical data rate of 434 kbps and maximal asymmetrical datarate of 723 kbps), and each hop channel has a bandwidth of 1 MHz.Gaussian frequency shift keying (GFSK) modulation is used. Data packetsinclude 1-2 byte payload headers for information about logical channeland payload length. Forward error correction with ⅔ rate may protect apayload of up to 339 bytes per packet. The link header for a packet has54 bits and contains control information and active addresses. Eachpacket typically is transmitted on a different hop frequency (channel).Two communicating Bluetooth devices are termed the master device and theslave device with the downlink being the transmissions from master toslave and the uplink being the transmissions from slave to master.

[0006] Another alternative for higher data rate wireless communicationis wideband code division multiple access (WCDMA). WCDMA is a proposedstandard useful for cellular telecommunications systems with data rateson the order of 144 kbps for high mobility applications, 384 kbps formore pedestrian-class mobility, and 2 Mbps for fixed environments.Quadrature phase shift keying (QPSK) type symbols multiplied by theappropriate spreading-scrambling codes modulating root-raised-cosinepulses are transmitted at a chip rate of 3.84 Mcps.

SUMMARY OF THE INVENTION

[0007] The present invention provides a wireless system with multipleantennas on either device and channel information for eigenvectortransmissions.

[0008] This has advantages including increased data rates in wirelesssystems such as Bluetooth and WCDMA.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009]FIG. 1 shows a preferred embodiment system.

[0010] FIGS. 2-3 illustrate a preferred embodiment mobile device.

[0011] FIGS. 4-5 are flow diagrams of preferred embodiment methods.

[0012]FIG. 6 shows a transceiver.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 1. Overview

[0013] Preferred embodiment wireless systems (e.g., Bluetooth, WCDMA,and so forth) provide a feedback of estimated (measured) channel fadingcoefficients to adjust the transmission parameters and thereby increasethe data rate for systems including transmitters having multipleantennas. When a transmitter has knowledge of the channel coefficients,it can transmit using antenna weightings to excite eigenvectors of thematrix product CC^(H) of the channel fading coefficient matrix C withits Hermitian conjugate C^(H). In particular, for a selected eigenvectorthe relative weightings of the baseband signals on the antennas of atransmitter's antenna array correspond to relative components of theeigenvector. Such eigenvectors are orthogonal and allow a receiver to beimplemented with a matched filter for each eigenvector. In addition,more bits can be transmitted on the dominant eigenvector and fewer bitson the other eigenvectors, which will increase the data rate. FIG. 5illustrates a preferred embodiment method in which a slave sendsorthogonal pilot symbols to a master which can analyze the receivedsignals to estimate (measure) the channel coefficients (i.e., find thematrix C) and thus estimate the eigenvectors and eigenvalues to use fora decision on symbol constellations for transmission on eigenvectors.

2. Two Antennas Preferred Embodiments

[0014]FIG. 1 schematically illustrates the downlink with both the masterdevice and the slave device having two antennas. The channelcoefficients (attenuation and phase shift) for the channel between theith antenna of the master to the jth antenna of the slave is denotedα_(ij) and these coefficients are fed back from slave to master andmaster to slave. The feedback of channel coefficients can either beexplicit as when channel measurements are fed back in a frequencydivision duplex (FDD) system or be implicit when channel measurements onone link are used to set the transmission parameters for the return linkas could be done with a time division duplex (TDD) system. Because thedownlink and uplink may be transmitted at different frequencies due tofrequency hopping, the fading will be different on each link. In orderfor the master to obtain knowledge of the downlink channel, the slavemust feed back channel measurement information; see FIG. 2. The mastercan send orthogonal pilots by transmitting pilot symbols from oneantenna at a time, and the slave then can feed back the downlink channelfading coefficients for every combination of transmit and receiveantennas. Alternatively, the slave can feed back the transmissionvectors that should be used, and these transmission vectors do not needto be eigenvectors. This feedback can be performed by sending one ormore bits during an uplink transmission.

[0015] In a TDD system in which the downlink and uplink occur at thesame frequency, the channel fading coefficients will be the same forboth links; see FIG. 3. Instead of using explicit feedback from theslave, the master can simply make channel measurements from the uplinktransmission and use these measurements to adjust the downlinktransmission; see FIG. 4. Bluetooth uses a frequency hopping TDDchannel, so the uplink and downlink will generally use differentfrequencies. In order to allow implicit feedback for Bluetooth, use amodified hopping sequence approach such as having the downlink repeatthe use of the prior uplink frequency.

[0016] Denote the baseband signals transmitted at the master's antennas1 and 2 as x⁽¹⁾* and x⁽²⁾*, respectively, with * denoting complexconjugate and the superscript a vector (antenna) component. The basebandsignals received at the slave's antennas 1 and 2, denoted r⁽¹⁾* andr⁽²⁾*, respectively, are thus

r⁽¹⁾*=x⁽¹⁾*α₁₁+x⁽²⁾*α₂₁

[0017] and

r⁽²⁾*=x⁽¹⁾*α₁₂+x⁽²⁾*α₂₂

[0018] where α_(ij) is the fading coefficient (e.g., attenuation andphase shift) for the channel between antenna i of the transmitter andantenna j of the receiver. This can be expressed in matrix notation asr^(H)=x^(H)C where ^(H) denotes Hermitian conjugate (complex conjugatetranspose), x^(H) and r^(H) are 1×2 vectors, and C is the 2×2 matrix ofchannel coefficients: $C = \begin{bmatrix}\alpha_{11} & \alpha_{12} \\\alpha_{21} & \alpha_{22}\end{bmatrix}$

[0019] With either explicit or implicit feedback, the master will knowthe fading coefficients {α_(ij)} for the downlink channel; and hence themaster can transmit signals which minimize the complexity of detectionby the slave, or which minimize the probability of detection error bythe slave, or which satisfy some other criteria. FIG. 6 illustrates amaster or slave (transceiver) device for eigenvector transmission anddetection.

[0020] In particular, let v₁ and v₂ be the eigenvectors and λ₁ and λ₂ bethe corresponding eigenvalues of the matrix CC^(H) and take λ₁ as theeigenvalue with the larger magnitude. Then when the master transmits adata stream (symbols) d(k) according to v₁ ^(H) (i.e., transmitcomponent d(k)v₁ ⁽¹⁾* from antenna 1 and component d(k)v₁ ⁽²⁾* fromantenna 2), the slave can detect with a matched filter simply bymultiplying the received vector by C^(H)v₁. That is, the transmission atthe master is d(k)v₁ ^(H), the channel applies C to yield a received 1×2vector (two slave antennas) d(k)v₁ ^(H)C, and the slave multiplies by(correlates with) the 2×1 vector C^(H)v₁ to yield d(k) v₁^(H)CC^(H)v₁=d(k)λ₁v₁ ^(H)v₁=d(k)λ₁, because v₁ is the eigenvector (ofunit magnitude) of CC^(H) for eigenvalue λ₁. And another data streamc(k) transmitted according to v₂ ^(H) will not interfere with detectionof the d(k) data stream because v₁ and v₂ are orthogonal as eigenvectorsof the Hermitian matrix CC^(H). In particular, transmitted c(k)V₂ ^(H)is received as c(k)v₂ ^(H)C, and then multiplication by C^(H)v₁ yieldsc(k)v₂ ^(H)CC^(H)v₁=c(k)λ₁v₂ ^(H)v₁=0. Further, the slave can alsodetect the transmission according to v₂ ^(H) with a matched filter ofmultiplication by C^(H)v₂: the data stream transmitted as d(k)v₁ ^(H)leads to d(k)v₁ ^(H)CC^(H)v₂=d(k)λ₂v₁ ^(H)v₂=0 again by orthogonality ofthe eigenvectors; and the data stream transmitted as c(k)v₂ ^(H) leadsto c(k)v₂ ^(H)CC^(H)v₂=d(k)λ₂v₂ ^(H)v₂=c(k)λ₂. Because |λ₁|≦|λ₂|, thetransmissions according to v₁ ^(H) will likely have a better signal tonoise ratio than the transmissions according to v₂ ^(H). Thus, maximizethe downlink capacity by using a water pouring solution: more bits aretransmitted on the eigenvector corresponding to the larger eigenvalue λ₁and fewer bits to the eigenvector of the smaller eigenvalue λ₂. That is,the symbols transmitted, d(k) and c(k), could be from different sizeconstellations: the constellation for the eigenvector of the largereigenvalue can be larger than the constellation for the othereigenvector(s). And the constellation size can be dynamically adjustedaccording to the quality of the channel associated with the eigenvector.This can be done by transmitting quadrature amplitude modulation (QAM)symbols on each eigenvector with the constellation size determined bythe quality of each eigenvector channel. The number of bits on eacheigenvector can be indicated in a packet header.

[0021] The eigenvalues for CC^(H) are fairly simple to express in termsof the channel coefficients. In particular, let a and b be the two rowvectors of the matrix C; then ${CC}^{H} = \begin{bmatrix}{a}^{2} & {\langle a \middle| b \rangle} \\{\langle b \middle| a \rangle} & {b}^{2}\end{bmatrix}$

[0022] and the two eigenvalues are [|a|²+|b|²±{square root}(4|

a|b

|²+(|a|²−|b|²)²)]/2. Of course, the eigenvalues sum to the trace of thematrix; namely, |a|²+|b|². And the case of a and b orthogonal (

a|b

=0), yields two eigenvalues |a|² and |b|² with eigenvectors a/|a| andb/|b|, respectively.

3. Varying Antenna Array Size Preferred Embodiments

[0023] The foregoing eigenvector mode transmission extends to three ormore antennas. Generally, for the case of M transmitter (master)antennas and N receiver (slave) antennas, the number of nonzeroeigenvalues (and thus the number of eigenvectors on which to transmitand have receiver matched filters to separate) equals the minimum of Mand N. Indeed, the downlink channel coefficient matrix C is M×N, so themaster's M-component transmission is received as N-components; the slavereceiver applies N×M matrix C^(H) to yield an M-component vector andcorrelates with the M-component eigenvectors of M×M matrix CC^(H) toproject the transmitted vector onto the eigenvectors and recover thetransmitted information. Analogously, the uplink (slave to master)channel coefficient matrix is the transpose of C, C^(T), which is N×Mand the slave's N-component uplink transmission is received as anM-component vector; the master applies the N×M Hermitian conjugatematrix (CT)^(H) to yield an N-component vector to correlate with theeigenvectors of the N×N matrix C^(T)C^(TH)=(C^(H)C)*. Note that thenontrivial eigenvectors of C^(H)C (and thus also (C^(H)C)*) and ofCC^(H) are related as images of each other: if CC^(H)v=λv, then w=C^(H)vis an eigenvector of C^(H)C by C^(H)Cw=C^(H)CC^(H)v=C^(H)λv=λw.

4. Maximized Minimum Distance Constellation Preferred Embodiments

[0024] Alternative preferred embodiments apply eigenvector weightedtransmissions (by the master) over multiple antennas with the weightingcriteria including maximization of the minimum distance betweenconstellation points (baseband symbols) at the receiver (slave).Maximizing the minimum constellation distance guarantees minimizing theraw error probability which is the important measure when no errorcorrection coding is used or when error correction coding is used buthard decision decoding is employed. In both of these cases presume nospace code is used. Also, different sized constellations will havedifferent numbers of nearest neighbors, so adjust for this by using thetheoretical error performance for each constellation.

[0025] The preferred embodiments in effect provide at least approximatesolutions when the master (transmitter) has M antennas and the slave(receiver) has N antennas to the problem of finding the M-dimensionaltransmission antenna weighting vector x_(i) ^(H) for the ith point inthe transmission constellation so the received N-dimensional vectorr_(i) ^(H)=x_(i) ^(H)C satisfies:$\max\limits_{\underset{constellation}{transmit}}{\min\limits_{i \neq j}{( {r_{i} - r_{j}} )^{H}( {r_{i} - r_{j}} )}}$

[0026] First consider transmitting K data streams (K symbols taken fromconstellations Q₁ . . . Q_(K)) with each data stream's weightingson theM antennas expressed as a linear combination of eigenvectors of theCC^(H) matrix; that is, x_(i) ^(H) as:$x_{i}^{H} = {{Q^{i}Y} = {\lbrack {Q_{1}^{i}Q_{2}^{i}\quad \ldots \quad Q_{K}^{i}} \rbrack \begin{bmatrix}{\sum{a_{m,1}v_{m}^{H}}} \\{\sum{a_{m,2}v^{H}}} \\{\sum{a_{m,3}v_{m}^{H}}} \\\cdots \\\cdots \\{\sum{a_{m,{K - 1}}v_{m}^{H}}} \\{\sum{a_{m,K}v_{m}^{H}}}\end{bmatrix}}}$

[0027] where Q^(i) is a 1×K vector of the ith points (symbols) of Kconstellations (Q_(k) ^(i) is the ith point of the kth constellation),the sums are over 1≦m≦M, v_(m) is the mth eigenvector of the M×M matrixCC^(H) where the elements of the M×N matrix C are the channelcoefficients {α_(ij)} for the channel from the ith transmit antenna tothe jth receive antenna, and a_(m,k) is the linear combinationcoefficient of the mth eigenvector when using the kth constellation.Note that Y, the column of sums, is a K×M matrix because eacheigenvector v_(m) ^(H) in the sums is a 1×M vector.

[0028] Thus the maximization becomes$\max\limits_{\underset{constellation}{transmit}}{\min\limits_{i \neq j}{( {Q^{i} - Q^{j}} )^{H}{YCC}^{H}{Y^{H}( {Q^{i} - Q^{j}} )}}}$

[0029] This maximization yields a maximum likelihood receiver, but athigh bit rates this might become extremely complex. Therefore a simplereceiver will be very attractive. So first consider the case ofa_(m,k=)0 except when m=k; this means transmissions using only the ktheigenvector for the kth constellation and this diagonalizes the K×Mmatrix Y. Such transmission of constellation points on the eigenvectorsallows use of a low-complexity matched filter receiver to recover thedata streams as previously described in the 2×2 case. Specifically,because v_(m) ^(H)CC^(H)v_(n)=0 except for m=n, there is no interferencefrom one data stream on one eigenvector to another data stream onanother eigenvector. Next, also presume M=N; that is, further considerthe case of the number antennas in the transmitter equal to the numberof antennas in the receiver. Then transmission of a total bit rate of Rmeans log₂(Π|Q_(m)|)=R where the product is over the M eigenvectors withconstellation Q_(m) on the mth eigenvector and where |Q_(m)| is thenumber of points in constellation Q_(m). For each possible distributionof constellation sizes the maximization is$\max\limits_{a_{m,m}}{\min\limits_{i \neq j}{{( {Q^{i} - Q^{j}} )^{H}\begin{bmatrix}{{a_{1,1}}^{2}\lambda_{1}} & \quad & 0 & \quad & \quad & \quad & 0 \\0 & \quad & {{q_{2,2}}^{2}\lambda_{2}} & \quad & \quad & \quad & 0 \\0 & \quad & 0 & \quad & \quad & \quad & 0 \\\quad & \ldots & \quad & \quad & \quad & \quad & \quad \\\quad & \ldots & \quad & \ldots & \quad & \quad & \quad \\0 & \quad & \quad & \quad & \quad & 0 & \quad \\0 & \quad & 0 & \quad & 0 & \quad & {{a_{M,M}}^{2}\lambda_{M}}\end{bmatrix}}( {Q^{i} - Q^{j}} )}}$

[0030] where λ_(m) is the eigenvalue for the mth eigenvector v_(m) ofCC^(H). Choosing all the constellations to have the same minimumdistance between points permits a solution to the maximization by theM−1 equations |a_(1,1)|²Xλ₁=|a_(2,2)|^(λ) ₂= . . . =|a_(M,M) ²λ_(M)subject to the total energy constraint equation; namely, if E is theaverage total energy and E_(m) is the average energy of the mthconstellation: ${\sum\limits_{m}{E_{m}{{m,m}}^{2}}} = E$

[0031] Solving the foregoing M equations yields all of the requiredlinear combination coefficients a_(m,k) for each distribution ofconstellations This allows calculation of the performance for everypossible constellation. These performance calculations providethresholds on the eigenvalues of the channel matrix at whichtransmission should be switched from one eigenvector to two eigenvectorsand from one constellation to another. The following sections haveexamples.

5. Two Antenna Diagonal Max-Min Preferred Embodiment

[0032] As an example of the foregoing maximization of minimum distancewith diagonal Y matrix method applied to the previously described twoantenna case: presume the data rate R=4 bits/transmission, thenmaximization provides:

[0033] (1) Transmit using a 16-QAM (4 bits per symbol) constellation onthe eigenvector v₁ corresponding to the larger magnitude eigenvalue λ₁when |λ₁|≧4|═₂| where λ₂ is the smaller magnitude eigenvalue.

[0034] (2) Transmit using two 4-QPSK (2 bits each symbol) constellationson the two eigenvectors v₁ and v₂ if |λ₁|<4|λ₂| with the linearcombination coefficients a_(m,k) as

a_(1,1)={square root}(λ₂/(λ₁+λ₂))

[0035] and

a_(2,2)={square root}(λ₁/(λ₁+λ₂))

[0036]FIG. 5 illustrates the transmitter's decision method.

6. Three Antenna Diagonal Max-Min Preferred Embodiment

[0037] As a further example of the foregoing maximization of minimumdistance with diagonal Y matrix method, apply the method to the threeantennas for both master and slave case with the eigenvalues of thechannel coefficient matrix CC^(H) as λ₁, λ₂, and λ3 such that|λ₁|≧|λ₂|≧|λ₃| and corresponding eigenvectors v₁, v₂, and v₃. Presumethe data rate R=6 bits/transmission, then the maximization provides:

[0038] (1) If |λ₁|≧16|λ₂, then transmit a 64-QAM (6 bits per symbol)constellation on the eigenvector v₁.

[0039] (2) If |λ₁|<16|λ₂ but |λ₁|≧4|λ₂|, transmit 16-QAM (4 bits)constellation on v₁ and transmit 4-QPSK (2 bits) constellation oneigenvector v₂.

[0040] (3) If |λ₁|<4|λ₂| transmit 4-QPSK (2 bits) constellation on eachof the three eigenvectors v₁, v₂, and v₃.

7. Two Antennas with Max-Min without Diagonal Preferred Embodiment

[0041] As an example of the foregoing maximization of minimum distancebut without the presumption of a diagonal Y matrix method and againapplied to the previously described two antenna case yields themaximization problem:$\max\limits_{a_{m,m}}{\min\limits_{i \neq j}{( {Q^{i} - Q^{j}} )^{H}\begin{matrix}\begin{bmatrix}{{a_{1,1}}^{2}\lambda_{1}{a_{2,1}}^{2}\lambda_{2}} & {{a_{1,1}a_{1,2}^{*}\lambda_{1}} + {a_{2,1}a_{2,2}^{*}\lambda_{2}}} \\{{a_{1,2}a_{1,1}^{*}\lambda_{1}} + {a_{2,2}a_{2,1}^{*}\lambda_{2}}} & {{{a_{1,2}}^{2}\lambda_{1}} + {{a_{2,2}}^{2}\lambda_{2}}}\end{bmatrix}\end{matrix}( {Q^{i} - Q^{j}} )}}$

[0042] where Q^(i) is a 2×1 vector of the two ith constellation points.Now assume that Q₁ and Q₂ are each 4-QPSK (2 bits) and the data rate R=4bits/transmission; then each eigenvector has a linear combination ofboth a Q₁ and a Q₂ constellation point and the maximization problem canbe solved. In particular, employing the notation A=(½+1/{squareroot}2)λ₂ and B=(½−1/{square root}2)λ₁, a solution is:

[0043] a_(1,1)=exp(jθ₁) {square root}(A/2)/(A+B)

[0044] a_(2,2)=exp(jθ₂) {square root}(A/2)/(A+B)

[0045] a_(1,2)=exp(jθ₃) {square root}(½−|a_(1,1)|)

[0046] a_(2,1)=exp(jθ₄) {square root}(½−|a_(2,2)|)

[0047] where θ₁−θ₂=3π/4 and θ₃−θ₄=−π/4.

[0048] In contrast, if a single 16-QAM constellation is used, then

[0049] a_(1,2)=a_(2,2)=0 (because no second constellation)

[0050] a_(1,1)=exp(jθ₁)

[0051] a_(2,1)=exp(jθ₂)/(2+{square root}3)

[0052] where θ₁−θ₂=π/12.

[0053] These results provide comparison of the performance in thealternative transmissions: two 2-bit symbols or one 4-bit symbol. Thetransmission with two less dense constellations is preferred when:

λ₁/λ₂<([1+2+{square root}3 ]/{square root}2−½−1/{squareroot}2)/(1/{square root}2 −½)

[0054] Thus a transmitter could (periodically, intermittently) estimateeigenvalues ratios and use a lookup table to decide on the bestconstellation distribution.

[0055] These results all satisfy the necessary Kuhn-Tucker conditionsfor minimum points.

[0056] The foregoing technique provides design methods for space-timecodes if the channel is known by assuming a block diagonal channelmatrix that is of size MT by NT where T is the length of the desiredspace-time code.

8. Systems

[0057] The circuitry to perform the multiple-antenna channel-eigenvectorBluetooth, WCDMA, or other wireless communication may use digital signalprocessors (DSPs) or general purpose programmable processors orapplication specific circuitry or systems on a chip such as both a DSPand RISC processor on the same chip with the RISC processor controlling.A stored program in an onboard or external ROM, flash EEPROM, orferroelectric RAM for a DSP or programmable processor could perform thesignal processing. Analog-to-digital converters and digital-to-analogconverters provide coupling to the real world, and modulators anddemodulators (plus antennas for air interfaces) provide coupling fortransmission waveforms. The encoded data can be packetized andtransmitted over networks such as the Internet.

9. Modifications

[0058] The preferred embodiments may be modified in various ways whileretaining the features of multiple antenna channel eigenvectoradaptation for dynamic symbol constellation selection.

[0059] For example, the number of bits (total bit rate R) andconstellations used could be varied, the ratio of eigenvalues for bitallocation decisions could be varied from the ideal to account for otheraspects such as computational complexity, updating channel coefficientmeasurements and estimates could be performed periodically or inresponse to coefficient drift or change or a combination with agingfactors. The maximizing constellation distributions and linearcombinations of eigenvectors for many sets of available constellationsin terms of the estimated eigenvalues can be stored in lookup tables (inboth transmitter and receiver) and provide for switching to alternativeconstellations and linear combinations of eigenvectors, and so forth.

What is claimed is:
 1. A method of wireless communication, comprising:(a) estimating at least one eigenvector of a matrix of communicationchannel coefficients for a channel between a first plurality of antennasand a second plurality of antennas; and (b) transmitting using saidfirst plurality of antennas with the relative weightings of basebandsignals on said first plurality of antennas corresponding to componentsof said at least one eigenvector.
 2. The method of claim 1, wherein: (a)said communication channel has MN coefficients, α_(ij) for i=1, . . . ,M and j=1, . . . N where M and N are positive integers, and α_(ij)relates to transmission from the ith antenna of a transmitter to the jthantenna of a receiver, and said matrix is CC^(H) where C is the M×Nmatrix with ith row and jth column entry α_(ij) and ^(H) is Hermitianconjugate.
 3. The method of claim 2, wherein: (a) said signals on saidantennas are a superposition of first signals weighted according to afirst eigenvector of CC^(H) plus second signals weighted according to asecond eigenvector of CC^(H) wherein the superposition depends uponfirst and second eigenvalues of CC^(H).
 4. The method of claim 3,wherein: (a) number of bits allocated between said first signals andsaid second signals depends upon the ratio of said first eigenvalue andsaid second eigenvalue.
 5. A method of wireless communication,comprising: (a) estimating eigenvectors of a matrix of communicationchannel coefficients between a transmitter with M antennas (M an integergreater than 1) and a receiver with N antennas (N an integer greaterthan 1); and (b) transmitting on said communication channel basebandsignals x1, . . . , xK (K a positive integer) with the relativeweightings of each of said signals among said antennas corresponding tocomponents of a linear combination of said eigenvectors of said matrix;(c) wherein said linear combinations of said signals maximize theminimum distance between received different signals at a receiver. 6.The method of claim 5, wherein: (a) said communication channel has MNcoefficients, α_(ij) for i=1, . . . , M and j=1, . . . N, and α_(ij)relates to transmission from the ith antenna of a transmitter to the jthantenna of a receiver, and said matrix is CC^(H) where C is the M×Nmatrix with ith row and jth column entry α_(ij) and ^(H) is Hermitianconjugate.
 7. The method of claim 5, further comprising: (a) repeatingstep (c) of claim 5 for a plurality of distributions of constellationsof symbols where each of said signals includes a symbol of aconstellation as a factor for a corresponding linear combination; and(b) using for said transmitting of step (b) of claim 5 the distributionof constellations and corresponding linear combinations from step (a) ofthis claim which has a largest maximum.
 8. The method of claim 5,wherein: (a) each of said linear combinations has a single nonzerocoefficient with a one-to-one relation between said K signals and K ofsaid eigenvectors.
 9. A transmitter, comprising: (a) antennas A1, . . ., AM where M is a positive integer greater than 1; (b) a channelanalyzer coupled to said antennas and operable to estimate eigenvaluesand eigenvectors of an M×M matrix derived from coefficients of acommunication channel from said antennas to a receiver; (c) a signalgenerator coupled to said antennas and to said channel analyzer andoperable to apply signals S1, . . . , SM to said antennas A1, . . . ,AM, respectively; wherein said signals are proportional to thecomponents of a linear combination of said estimated eigenvectors. 10.The transmitter of claim 9, wherein: (a) said channel analyzer operableto compare the magnitudes of a first eigenvalue and a second eigenvalue;and (b) said signal generator allocates bits to be transmitted betweenfirst signals S′1, . . . , S′M and second signals S″1, . . . , S″Maccording to the results of step (a), wherein said first signals S′1, .. . , S′M are transmitted according to the components of said firsteigenvector and said second signals S″1, . . . , S″M are transmittedaccording to the components of said second eigenvector and the signalsS1, . . . , SM include the sums S′1+S″1, . . . , S′M+S″M, respectively.11. The transmitter of claim 9, wherein: (a) when said communicationchannel connects said antennas A1, . . . , AM with antennas B1, . . . ,BN of a receiver for N a positive integer, said M×M matrix is CC^(H)where C is an M×N matrix with element m,n an estimate of a channelcoefficient from antenna Am to antenna Bn, and where C^(H) is theHermitian conjugate of C.
 12. The transmitter of claim 9, wherein: (a)said signal generator includes information of constellationdistributions and linear combinations of eigenvectors in terms ofeigenvalues.